Customer lifetime value (CLV) – commonly referred to as lifetime customer value or user lifetime value, is the projected net profit that will be derived from the entire future relationship with the customer. CLV is based on predictive analytics techniques – because it projects on future spending of customers – and is mostly made use of by companies in relationship-focused business with a contractual base such as insurance companies and banks.
CLV is considered an aspect of creating marketing strategies. This is because from examining past customer spending trends, one can project on how much they will spend in the future. Once a marketer has this knowledge, they can determine how much they can spend to advertise to a customer without exceeding what the customer will spend on buying their product. This leads to another point: CLV projections can also help with the segmentation of customers to define and understand their common characteristics. Segmentation is when customers are classified based on different parameters (depending on the company) such as age, class of goods purchased and product type. Segmentation comes in handy when streamlining marketing plans. This means that a company can outline different marketing strategies for different market segments – that is, spend more to retain customers who have greater purchasing power, instead of throwing away money on customers who will not spend in return. This strategy also helps marketers put a cap on how much they should spend to retain customers.
Other than projecting spending limits, CLV matrices can also be used to determine the spending limits for acquiring new customers. CLV projections can also be used to monitor how effective previously applied marketing strategies to comprehend how effective they are, and to review these strategies as need be. CLV also helps marketers on the long-term value of customers rather spending money on getting new customers who will not have as much value in the future.
The factors that are taken into consideration when calculating CLV are: gross contribution per customer per year (GC), retention rate per customer per year (r), number of years the customer is projected to be retained (n), and the yearly discount rate (d).
While there are various formulae for calculating CLV, a simple formula is computed as:
CLV does have its drawbacks, primarily because it is a projection and not an absolute prediction of customer behavior. CLV can also put a too high value on current customers at the expense of future customers.